Certain documents as well as unstructured data can be complex. The complexity of the data arises from a variety of factors, including but not limited to the length of the document or volume of the data, the manner in which data is generated for a given document, the manner in which data is organized or presented in a given document, monotonous or repetitive data interspersed with hard to find information of interest, and cryptic or ambiguous representation of the data.
Log data, event records, transaction history, status monitoring log, trouble tickets, and bug reports are some examples of complex documents that exhibit some combination of these and other complexity factors. For example, software support teams use trouble tickets to track the problems reported by clients and the various interactions between the support engineers and the client for the duration of the problem. Diagnosing and solving complex problems that involve multiple components or products can take months, and the problem record can grow to be hundreds of pages long. The post-problem analysis process uses the problem record to understand why the problem was so difficult to diagnose, so that the root cause of the problem can be addressed.